from numpy import *
import operator
def createDataSet():
    group = array([[1.0,1.1],[1.0,1.0],[0,0],[0,0.1]])
    labels = ['A','A','B','B']
    return group, labels

def classify0(inX, dataSet, labels, k):
    dataSetSize = dataSet.shape[0]
    # 这里shape函数返回的是
    # dataSet的格式大小，而shape[0]表示的是dataSet的行数，
    # 这里行数代表的是数据集的数目。
    print(tile(inX, (dataSetSize,1)))
    diffMat = tile(inX, (dataSetSize,1))-dataSet
    # diffMat = tile(inX, (dataSetSize,1)) - dataSet
    # diffMat = tile(inX, (dataSetSize,1)) – dataSet
    sqDiffMat = diffMat**2
    sqDistances = sqDiffMat.sum(axis=1)
    distances = sqDistances**0.5
    sortedDistIndicies = distances.argsort()
    classCount={}
    for i in range(k):
        voteIlabel = labels[sortedDistIndicies[i]]
        classCount[voteIlabel] = classCount.get(voteIlabel,0) + 1
    sortedClassCount = sorted(classCount.items(),
    key=lambda x:x[1], reverse=True)
    print(sortedClassCount)
    return sortedClassCount[0][0]
group,labels =  createDataSet()
rest = \
classify0([0,0], group, labels, 3)
print(rest)